This disclosure is generally in the field of nucleic acid characterization and analysis, and specifically in the area of analysis and comparison of genes, gene expression patterns, nucleic acid samples, genomes, and genetic biomarkers.
The analysis of gene-expression and genome patterns is one of the most promising approaches for studying cellular molecular circuitry, biological diversity, and developmental biology. These studies may elucidate the identity and role of molecular targets, which will subsequently play an important role in developing efficacious human and veterinary therapeutics; novel technologies for biodefense; biological agents for bioremediation; and agricultural advances including predator resistant strains, superior crop yields, and increased shelf life. Furthermore, routine medical diagnostics will add genetic profiling assays for drug administration and patient therapeutic monitoring.
Differential Display and DNA Microarray gene expression profiling techniques have emerged as the predominate methods for whole genome gene expression analysis. These technologies measure changes in gene expression among cellular states to determine life processes. Exemplary conditions that effect cellular states include temporal, spatial, and experimental treatments, or any combination thereof. Types of state changes observed include genome-wide effects of known regulators or transcription factors, the biological components of the cellular machinery that generate the genomic signals, and measurements of over- or under-active regulators or transcription factors, for example. In addition, these technologies may be employed in the study of comparative genomics and the discovery of genetic biomarkers.
Classical approaches to gene-expression analysis, such as northern blotting or plaque hybridization, are time-consuming and material-intensive methods to analyze mRNA-expression patterns. Additionally, these early methods encountered problems with cDNA-probe complexity for differential hybridization. Subtractive hybridization was developed to address this problem using a method to enrich for cDNA targets that represent mRNAs that are uniquely expressed in one cell but not in another. This method reduced the complexity, leaving behind only single-stranded cDNAs that represented a few differentially expressed genes.
The Differential Display (DD) method overcame the limitation of these earlier methods that could be error-prone, insensitive, non-systematic, and laborious. Furthermore, DD is an “open system” not requiring any knowledge of RNA or gene sequences. DD simplified the experimental process with a one-tube method and increased the speed in the identification of expressed genes. DD systematically produces sets of nucleic acid fragments by amplifying anchored mRNA with a primer of arbitrary sequence. The fragments from each primer are displayed side-by-side using denaturing polyacrylamide gel electrophoresis. Comparison of DNA fragment patterns between or among relevant RNA samples indicate differences in gene expression.
Variations in the original DD protocol used strategies employing variations of enzyme sets, primers sets and combinations thereof. These derivate methods of DD included RFLP-Based DD strategies, Targeted DD, Integration of Subtractive Hybridization, and Integration of DD with DNA Microarrays.
SAGE (Serial Analysis of Gene Expression) is an open system sequence-based approach to identify differentially expressed genes. In this method, short (10-14 base pair) nucleic acid tags are generated by restriction digestion, amplified by PCR and ligated, producing concatemers, which are further analyzed by electrophoretic sequencing methods. The tag identities are sufficient in unequivocally corresponding to genes. Furthermore, the frequency of the tags is a measure of their expression level. A limitation of SAGE is that the corresponding gene can be identified only for the tags deposited in public repositories, imposing a dependency on available databases. Variants have been published that circumvent some limitations of SAGE.
High-density DNA microarrays advanced gene expression profiling technology, enabling simultaneous analysis from tens of thousands of genes on a standard laboratory microscope slide. cDNA or oligonucleotide capture probes of known sequence are systematically deposited at known locations on a solid support, i.e., “chips”. The capture probe positions are commonly referred to as addresses. Fluorescence labeled mRNA or cDNA targets are hybridized to complementary capture probes, signal detected by multi-color microarray laser scanner and displayed with image analysis software. Predominantly, DNA microarrays are closed systems, requiring the knowledge of RNA or gene sequences.
Other innovative open systems for gene-expression profiling, producing sequence tags from RNA or cDNA using various adapter driven methods, have been described. These methods use a variety of strategies whereby a cDNA sample is systematically digested into fragment pools; a fragment is ligated to one or more adapters, and amplified. Subsequent steps include sorting the tags by means of adapter mediated indexing. All these methods are significant improvements over DD by explicitly providing tag sequence information.